google/active-learning

Health v2 · maintenance only

Flags: no_releases archived

Adoption not part of the score

1162 stars · 204 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python module for running experiments comparing different active learning algorithms on benchmark datasets. It provides a main experiment runner, dataset download utilities, and a collection of sampling methods that can be mixed together.

Use cases

• compare active learning sampling strategies on benchmark datasets
• run active learning experiments with tensorflow models
• benchmark margin sampling vs uncertainty sampling
• evaluate labeling efficiency of sampling methods
• experiment with mixtures of active learning samplers
• download and preprocess datasets for active learning research

When to choose

• you need a ready-made harness to benchmark active learning algorithms
• you want to reproduce or extend active learning research experiments
• you need many sampling methods implemented in one place

When to avoid

• you need production active learning pipelines integrated into your ML stack
• you want a maintained library with recent updates
• you need deep learning frameworks other than TensorFlow

Facets

library · maturity maintenance

machine-learning benchmarking data-science machine-learning artificial-intelligence python windows active-learning experiment-framework sampling-methods tensorflow research-tool research linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google/active-learning")